For many organizations, big data's quandary isn't corralling information, but rather figuring how to actualize its value in a timely way or, in some cases, immediately.
After all, what's the point of data if not to help make discernable markers on strategy, decision making and on-the-fly operational modifications? As such, without investing in specialists and additional computing power there still are few suitable ways for businesses to harness data's insight potential.
The challenge is to make sense of volumes of data generated from machines and sensors and act on what the data reveals, hopefully resulting not only in improved operations, but also more revenue and lower costs. Unfortunately, as with most things, it's easier said than done.
In other words, the collecting is fine. The useful analysis - maybe not so much. Where and how solution providers fit into the equation is still a work in progress, but steps in that direction to establish need already are in the making.
Indeed, consultant McKinsey last year sampled a small group of business analytics leaders engaged with big data and advanced analytics and found that 75 percent said they'd achieved less than one percent of revenue or cost improvement, wrote David Court, a McKinsey director, in a McKinsey Quarterly report.